Create app.py

app.py

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+import gradio as gr
+from transformers import MarianMTModel, MarianTokenizer
+
+# Load Hugging Face translation model
+model_name = "Helsinki-NLP/opus-mt-en-ur"  # ✅ Pretrained English to Urdu Model
+tokenizer = MarianTokenizer.from_pretrained(model_name)
+model = MarianMTModel.from_pretrained(model_name)
+
+# Define the translation function
+def translate_to_urdu(text):
+    # Tokenize input text
+    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
+    
+    # Generate translation
+    translated = model.generate(**inputs)
+    
+    # Decode the translation
+    output_text = tokenizer.decode(translated[0], skip_special_tokens=True)
+    return output_text
+
+# Create a Gradio interface for the translator
+translator = gr.Interface(
+    fn=translate_to_urdu,
+    inputs=gr.Textbox(lines=2, placeholder="Enter English text..."),
+    outputs="text",
+    title="English to Urdu Translator",
+    description="Enter English text and get the Urdu translation instantly.",
+    theme="soft",
+)
+
+# Launch the Gradio app
+translator.launch()